Use of turbulent flow statistical properties for correcting erroneous velocity vectors in PIV

Philippe Druault; Philippe Guibert

doi:10.1016/j.crme.2004.04.006

Use of turbulent flow statistical properties for correcting erroneous velocity vectors in PIV

Presented by: Évariste Sanchez-Palencia

Philippe Druault ¹ ; Philippe Guibert ¹

¹ Laboratoire de mécanique physique, CNRS UMR 7068, université Pierre et Marie Curie, 2, place de la gare de ceinture, 78210 Saint Cyr l'École, France

Comptes Rendus. Mécanique, Volume 332 (2004) no. 9, pp. 731-736.

Abstract
Résumé

For particular turbulent flows, PIV measurements technique provides more than 10% of spurious velocity vectors at each time step. To correct these vectors, we propose to use the Linear Stochastic Estimation (LSE) dealing with the spatial correlation tensor of the velocity. If this tensor cannot be determined in some measurement zones, Proper Orthogonal Decomposition is used to model this tensor. Both reconstruction methodologies are tested from PIV measurements performed in a Spark Ignition engine flow. We show that for coherent structures analysis, the LSE reconstruction method provides better results than classical mathematical interpolation methods.

Les mesures PIV peuvent entraı̂ner pour des écoulements turbulents particuliers près de 10 % de vecteurs vitesse erronés. Pour corriger ces vecteurs, on propose d'utiliser l'Estimation Stochastique Linéaire basée sur le tenseur de corrélation spatiale de vitesse. Si ce tenseur n'est pas partout accessible, la Décomposition Orthogonale aux valeurs Propres est alors utilisée pour reconstruire ce tenseur. Une validation de ces procédures de reconstruction réalisée à partir de mesures PIV en écoulement de moteur a ainsi montré l'intérêt pour l'analyse des structures cohérentes d'utiliser la LSE par rapport aux méthodes d'interpolations mathématiques couramment utilisées.

Received: 2003-11-12
Accepted: 2004-04-27
Published online: 2004-07-23

DOI: 10.1016/j.crme.2004.04.006

Mots-clés : Turbulence, Structures cohérentes, PIV, Estimation Stochastique, Décomposition Orthogonale aux valeurs propres
Mots-clés : Turbulence, Coherent structures, PIV, Stochastic Estimation, Proper Orthogonal Decomposition

Author's affiliations:

Philippe Druault ¹; Philippe Guibert ¹

¹ Laboratoire de mécanique physique, CNRS UMR 7068, université Pierre et Marie Curie, 2, place de la gare de ceinture, 78210 Saint Cyr l'École, France

@article{CRMECA_2004__332_9_731_0,
     author = {Philippe Druault and Philippe Guibert},
     title = {Use of turbulent flow statistical properties for correcting erroneous velocity vectors in {PIV}},
     journal = {Comptes Rendus. M\'ecanique},
     pages = {731--736},
     publisher = {Elsevier},
     volume = {332},
     number = {9},
     year = {2004},
     doi = {10.1016/j.crme.2004.04.006},
     language = {fr},
}

TY  - JOUR
AU  - Philippe Druault
AU  - Philippe Guibert
TI  - Use of turbulent flow statistical properties for correcting erroneous velocity vectors in PIV
JO  - Comptes Rendus. Mécanique
PY  - 2004
SP  - 731
EP  - 736
VL  - 332
IS  - 9
PB  - Elsevier
DO  - 10.1016/j.crme.2004.04.006
LA  - fr
ID  - CRMECA_2004__332_9_731_0
ER  -

%0 Journal Article
%A Philippe Druault
%A Philippe Guibert
%T Use of turbulent flow statistical properties for correcting erroneous velocity vectors in PIV
%J Comptes Rendus. Mécanique
%D 2004
%P 731-736
%V 332
%N 9
%I Elsevier
%R 10.1016/j.crme.2004.04.006
%G fr
%F CRMECA_2004__332_9_731_0

Philippe Druault; Philippe Guibert. Use of turbulent flow statistical properties for correcting erroneous velocity vectors in PIV. Comptes Rendus. Mécanique, Volume 332 (2004) no. 9, pp. 731-736. doi : 10.1016/j.crme.2004.04.006. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.1016/j.crme.2004.04.006/

References
Cited by

[1] R.D. Keane; R.J. Adrian Optimization of particle image velocimeters. Part I : Double pulsed systems, Meas. Sci. Techn., Volume 1 (1990), pp. 1202-1220

[2] J. Nogueira; A. Lecuona; P.A. Rodriguez Data validation, false vectors correction and derived magnitudes calculation on PIV data, Meas. Sci. Techn., Volume 8 (1997), pp. 1493-1501

[3] J. Westerweel Efficient detection of spurious vectors in particle image velocimetry data, Exp. Fluids, Volume 16 (1994), pp. 236-247

[4] G.R. Spedding; J.M. Rignot Performance analysis and application of grid interpolation technique for fluid flows, Exp. Fluids, Volume 15 (1993), pp. 417-430

[5] I. Fujita; T. Kaizu Correction method of erroneous vectors in PIV, J. Flow Visu. Image Proc., Volume 2 (1995), pp. 173-185

[6] I. Kimura Application of artificial neural networks and genetic algorithm to PIV, Proceedings of ASME/JSME FED Summer Meeting, San Francisco, 1999

[7] R.J. Adrian On the role of conditional averages in turbulence theory, Proceedings of the 4th Biennal Symposium on Turbulence in Liquids, 1975

[8] Ph Druault; J. Delville Representation of the spatial correlation tensor of the velocity in free turbulent flows, C. R. Acad. Sci. Paris, Sér. IIb, Volume 328 (2000), pp. 135-141

[9] J.L. Lumley Stochastic Tools in Turbulence, Academic Press, New York, 1970

[10] Ph Guibert; L. Lemoyne Dual particle image velocimetry for transient flow field measurement, Exp. Fluids, Volume 33 (2002), pp. 355-367

[11] Ph. Druault, Développement d'interfaces expérience/simulation. Application à l'écoulement de couche de mélange plane turbulente, Ph.D. Dissertation, University of Poitiers, France, 1999

Cited by Sources:

Comments - Policy